Category: Economics
Minimum wage hikes and robots
This paper studies how minimum wage policy affects firms’ adoption of automation technologies. Using both state-level measures of robot exposure and novel plant-level data on industrial robot imports linked to U.S. Census microdata from 1992-2021, we show that increases in minimum wages raise the likelihood of robot adoption in manufacturing. Our preferred identification exploits discontinuities at state borders, comparing otherwise similar firms exposed to different wage floors. Across specifications, a 10 percent increase in the minimum wage increases robot adoption by roughly 8 percent relative to the mean.
That is from Erik Brynjolfsson, et.al., including Andrew Wang. Via the excellent Kevin Lewis.
By the way, a photo from our textbook Modern Principles of Economics:
Changes in the Gender Wage Gap for Business Professionals
In the United States, much of the gap in earnings between men and women is due to the persistent gap for high wage earners. This paper explores changes in the gender wage gap for MBAs graduating from a large public university over 30 years. We document large gender wage gaps on average, which grow in the course of men’s and women’s careers. Comparing graduates at identical career stages across time periods to address composition concerns, we show that the raw gender wage gap has shrunk by 33 to 50 percent over the last two decades. Additionally, the temporal pattern of the gap has fundamentally shifted: while gaps only emerged over time in earlier decades, significant gaps now emerge immediately. Convergence in labor supply factors, particularly hours worked, explains much of the narrowing gap, alongside shifts in industry composition. However, unexplained wage gaps persist for recent graduates from the very start of their careers, suggesting different underlying mechanisms across cohorts. These findings highlight both progress in gender wage equity among business professionals and concerning patterns that emerge earlier in careers than in previous decades.
That is from a recent NBER working paper by
The import of cross-task productivity
Given that LLMs seem to be able to automate so many small tasks, why don’t we see large productivity effects?
I drafted a short paper recently exploring the possibility that it’s for the same reason (or at least one of the reasons) that labor is typically bundled into multi-task jobs, instead of transacted by the task, in the first place: because performing a task increases one’s productivity not only at the task itself but at related tasks.
For example, say you used to spend half your time coding and half your time debugging, and the LLM can automate the coding but you still have to do the debugging. If you’re more productive at debugging code you write yourself, this (1) explains why “coder” and “debugger” aren’t separate jobs, and (2) predicts that the LLM won’t save half your time. If you’re half as productive at debugging code you didn’t write, or less, the LLM saves you no time at all.
So I was excited to see @judyhshen and @alextamkin’s paper from a week or two ago finding basically just that!
At least the way I’m thinking about it, “cross-task learning” should make the productivity impacts of automating tasks more convex: – Automating the second half of a job should be expected to have much more of an impact than automating the first half; and – If the machines can learn from their and each others’ experience, as a worker learns by doing from her own experience, then automating two jobs will have more than twice the impact of automating one.
That is from Philip Trammell. Here is his short piece. Here is the Shen and Tamkin paper. This is all very important work for why the AI growth take-off will be much slower than the power of the models themselves might otherwise indicate. The phrase “…and then all at once” nonetheless applies. But when?
These short pieces and observations are likely among the most important outputs economists will produce this year. But are they being suitably rewarded?
Oliver Kim reviews *How Africa Works*
That is the new book by Joe Studwell, my podcast with him should be coming out pretty soon. Here is Oliver’s new review. Excerpt:
Botswana is Studwell’s poster child for a successful democratic developmental coalition. (For this reason, it featured heavily in Acemoglu and Robinson’s Why Nations Fail as an example of “inclusive institutions”.)
Under the sound leadership of Seretse Khama, local chiefs were carefully co-opted at independence and the Botswana Democratic Party built up into a genuine national force. Khama also created a capable civil service, initially staffed by remaining Europeans, but gradually Africanized with sterling Batswana talent. This meant that when diamonds were discovered just around independence, the windfall was carefully managed, avoiding the worst effects of Dutch Disease. These mining revenues helped raise Botswana to upper middle-income status, making it the fourth-richest country in continental Africa.
Botswana’s chief failing, in Studwell’s view, was adhering too much to responsible policy orthodoxy—i.e., not enough industrial policy. There was no vision for large-scale industrialization, no coherent plan to create large numbers of factory jobs. Moreover, the political dominance of large cattle owners (Botswana was a society of pastoralists rather than farmers) meant that redistribution was never in the cards. The result is a relatively rich society, but one that is highly unequal.
You will be hearing my views on these issues soon enough. Oliver, of course, writes one of the very best Substacks in all of economics.
Past Automation and Future A.I.: How Weak Links Tame the Growth Explosion
From Charles I. Jones and Christopher Tonetti:
How muchof past economic growth is due to automation, and what does this imply about the effects of A.I. and automation in the coming decades? We perform growth accounting using a task-based model for key sectors in the U.S. economy. Historically, TFP growth is largely due to improvements in capital productivity. The annual growth rate of capital productivity is at least 5pp larger than the sum of labor and factor-neutral productivity growth. The main benefit of automation is that we use rapidly-improving machines instead of slowly-improving humans on anincreasing set of tasks. Looking to the future, we develop an endogenous growth model in which the production of both goods and ideas is endogenously automated. We calibrate this model based on our historical evidence. Two key findings emerge. First, automation leads economic growth to accelerate over the next 75 years. Second, the acceleration is remarkably slow. By 2040, output is only 4% higher than it would have been without the growth acceleration, and by 2060 the gain is still only 19%. A key reason for the slow acceleration is the prominence of “weak links” (an elasticity of substitution among tasks less than one). Even when most tasks are automated by rapidly improving capital, output is constrained by the tasks performed by slowly-improving labor.
And an important sentence from the paper itself:
…, the key gain from automation is that it allows production of a task to shift away from slowly-improving human labor to rapidly-improving machines.
The authors stress that those are preliminary results, and the numbers are likely to change. For the pointer I thank the excellent Kurtis Hingl, who is also my research assistant.
*The Almighty Dollar*
The author is Brendan Greeley, and the subtitle is 500 Years of the World’s Most Powerful Money. A very well-timed book, excellent on the history of the dollar as it spans the centuries, I was happy to write a blurb for it.
Immigration and health for elderly Americans
We measure the impact of increased immigration on mortality among elderly Americans, who rely on the immigrant-intensive health and long-term care sectors. Using a shift-share approach we find a strong impact of immigration on the size of the immigrant care workforce: admitting 1,000 new immigrants would lead to 142 new foreign healthcare workers, without evidence of crowd out of native health care workers. We also find striking effects on mortality: a 25% increase in the steady state flow of immigrants to the US would result in 5,000 fewer deaths nationwide. We identify reduced use of nursing homes as a key mechanism driving this result.
That is from a new NBER working paper by
Poverty reduction is slowing down
The basic reason why I’m not very optimistic about Africa’s growth prospects under current conditions is that the track record is extremely poor, and there’s little reason to think that anything fundamental has changed. Between 1992 and 2022, median income in China grew at an average annualized rate of 6.6 percent per year; in India it grew at a rate of 2.9 percent per year; but in sub-Saharan Africa it grew at just 1.6 percent per year, less than the rate of growth exhibited in the famously stagnant (and much wealthier) United Kingdom. But in much of the continent the picture has been worse than mere slow growth. Some countries that were relatively stable a few decades ago are now in a state of apparently permanent civil conflict, as in the Democratic Republic of the Congo (DRC) or Somalia; while other countries that have been blessed by relative stability, such as Kenya, Malawi, or Zambia, are poorer on a median income basis than they were in the ‘80s or ‘90s.
There are many things to say about why economic growth in Africa has been so disappointing, from the primacy of extractive resource sectors to the dominance of predatory elites to the poor state of human capital to the ubiquity of corruption to the absence, in many places, of a strong state monopoly on legitimate violence. But these are merely surface-level problems: the fact that these conditions exist in nearly every country in Africa, despite their widely varying historical experiences and the different ideologies with which their states have experimented, suggests that the fundamental problem is not so much with the state but the society underlying the state. If you were to describe this problem briefly, you could do quite well with something like “kinship groups crowd out effective institutions.” African societies have extraordinarily strong kinship ties, such that impersonal institutions and relationships are systematically subordinated to family, clan, and ethnic loyalties; as a result many African societies have found it extraordinarily difficult to build effective states and civil societies that are capable of doing what states and civil societies are supposed to do. (For a more complete elaboration of this view, see my article on why African nations don’t have large firms.) Solving that problem took Europe roughly a millennium; and that was when people didn’t have access to AK-47s.
Here is more from David Oks.
This security will be pricing *something* (but what?)
Alphabet has lined up banks to sell a rare 100-year bond, stepping up a borrowing spree by Big Tech companies racing to fund their vast investments in artificial intelligence this year.
The so-called century bond will form part of a debut sterling issuance this week by Google’s parent company, according to people familiar with the matter. Alphabet was also selling $15bn of dollar bonds on Monday and lining up a Swiss franc bond sale, the people said.
Century bonds — long-term borrowing at its most extreme — are highly unusual, although a flurry were sold during the period of very low interest rates that followed the financial crisis, including by governments such as Austria and Argentina.
Here is more from the FT, let us see how the yield comes in…
For a long time I have been predicting the return of phrenology
Yup:
Human capital—encompassing cognitive skills and personality traits—is central for labor-market success, yet personality remains difficult to measure at scale. Leveraging advances in AI and comprehensive LinkedIn microdata, we extract the Big 5 personality traits from facial images of 96,000 MBA graduates, and demonstrate that this novel “Photo Big 5” predicts school rank, job matching, compensation, job transitions, and career advancement. The Photo Big 5 provides predictive power comparable to race, attractiveness, and educational background, and is only weakly correlated with cognitive measures such as test scores. We show that individuals systematically sort into occupations where their personality traits are valued and earn higher wages when traits align with occupational demands. While the scalability of the Photo Big 5 enables new academic insights into the role of personality in labor markets, its growing use in industry screening raises important ethical concerns regarding statistical discrimination and individual autonomy.
That is from a new NBER working paper by
You gotta’ believe!
AI technology can generate speculative-growth equilibria. These are rational but fragile: elevated valuations support rapid capital accumulation, yet persist only as long as beliefs remain coordinated. Because AI capital is labor-like, it expands effective labor and dampens the normal decline in the marginal product of capital as the capital stock grows. The gains from this expansion accrue disproportionately to capitalists, whose saving rate rises with wealth, raising aggregate saving. Building on Caballero et al (2006), I show that these features generate a funding feedback—rising capitalist wealth lowers the required return—that can produce multiple equilibria. With intermediate adjustment costs, elevated valuations are the mechanism that sustains a transition toward a high-capital equilibrium; a loss of confidence can precipitate a self-fulfilling crash and reversal.
That is from a new NBER working paper by Ricardo J. Caballero.
Sebastian Galiani on the Marginal Revolution
The most successful economics blog in the world is called Marginal Revolution.
That is not an accident….Consider a few common mistakes that reappear whenever marginal thinking is abandoned:
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- Treating the owner’s biography—wealth, identity, status—as if it entered the firm’s marginal conditions. It does not.
- Confusing redistribution with allocation. Redistribution is a legitimate political choice, but it should not be smuggled into production decisions where it distorts incentives and blocks reallocation.
- Ignoring opportunity cost. Resources used to sustain one activity are resources not used elsewhere. The relevant question is always: what is the next best alternative?
- Believing that efficiency is static. In reality, efficiency is dynamic, and depends precisely on the ability of resources to move when margins change.
One of the most uncomfortable implications of marginal analysis is that reallocation is essential. Labor and capital must sometimes leave declining uses so they can enter expanding ones. That process is rarely smooth, and never painless. But blocking it does not make an economy more humane; it makes it poorer.
The twentieth century gave this insight a name. Joseph Schumpeter called it creative destruction. János Kornai warned that when losses are systematically covered—when budget constraints are soft—adjustment never happens, inefficiency becomes chronic, and stagnation follows.
Marginal analysis explains why. If losses have no consequences, margins lose meaning. Prices stop signaling scarcity. Productivity differences stop guiding allocation. The economy becomes a museum of preserved structures rather than a system that adapts.
Excellent throughout, here is the link.
FT podcast with Soumaya Keynes
Mostly about the economics of food, this is from their episode summary:
If you want to understand food – and eat better – economics is a good place to start. How do immigration patterns shape a country’s cuisine? How do labour laws make our working lunches worse? And why do strip malls serve such good grub?
About 33 minutes, here are the links:
Spotify: https://open.spotify.com/episode/30oLOLQZvGmvxJzA31X3qK
Can government coerce women into having more babies?
To illustrate this challenge of measurement and inference, Figure 7 presents Romanian birth rates before, during, and after the imposition of an infamously coercive policy aimed at raising births. In 1966, a dictatorial government imposed Decree 770, which banned abortion and made modern contraception effectively inaccessible. The figure extends an idea from Sobotka, Matysiak, and Brzozowska (2019), which compares cohort and period fertility rates in Romania over a similar evaluation window. We add data from Bulgaria, Romania’s neighbor that was also communist during the time of the policy and that might plausibly serve as a control, shedding light on what course Romanian fertility might have followed after 1967 if not for the policy. Panel A plots period birth rates in the two countries and shows that Romania and Bulgaria had substantially similar trends and levels in period total fertility rates before and after the Romanian policy window. Focusing on panel A of Figure 7, it is clear that birth rates in Romania changed dramatically following the start of the policy, as families were taken by surprise. TFR nearly doubled in the year that followed. The sharp timing of this apparent impact following the policy change, together with the availability of data from neighboring Bulgaria to serve as a control, suggests the possibility of a difference-in-differences analysis comparing birth rates pre– and post–Decree 770 in Romania and Bulgaria.
But while such an analysis could answer the narrow question of the causal effect of Decree 770 on the total fertility rate in 1967, it may nonetheless reveal little in terms of the impact of the policy on the number of children Romanian women had over their lifetimes. After the initial rise in TFR, birth rates soon began falling quickly in Romania, as behavior adapted to the new policy regime. If, for example, an unexpected pregnancy results in a birth at a young age in 1968, a woman may choose and succeed at reducing the probability of a pregnancy in subsequent years, and still achieve the same lifetime count of children.
For a discussion of the theoretically ambiguous impact of abortion restrictions on birth rates, see Lawson and Spears (2025). Of course, the extent of persistence from period fertility to completed fertility depends on the details: A shock that encourages earlier-than-desired births, as Romania’s might have, allows for adjustment later in life. But it may be harder, later in life, to adjust for a policy or event shock that leads to fewer births early in life.Panel B of Figure 7 plots completed cohort fertility. As in earlier figures, cohorts are plotted along the horizontal axis according to the year in which they turned 30. Although Romanian completed cohort fertility began at a higher level than in Bulgaria over the available data series, completed cohort fertility in Romania did not maintain a sizable upward trend relative Bulgaria during the period that Decree 770 was in force.
That is from the recent Geruso and Spears JEP survey piece on whether we can expect fertility rates to rebound in the future. By the way, after Hungary’s subsidy-driven baby boom, the country is now having a baby bust, it is possible that similar mechanisms are operating.
The economics of the NBA trading deadline (from my email)
From an anonymous correspondent:
Perhaps, as NBA fan, there’s a column to be written about the incentives that drove the NBA trade market: namely the all-out search to avoid/get out of the luxury tax and the looming “tank” battle among the 6 worst teams. These are both direct results of the recent NBA collective bargaining agreement changes. Of course, as these attempts to regulate behavior go, the ‘benign’ intentions of the regulators are far different from the actions of the rational actors having to live within the system.
The funniest behavior-following-incentive example was orchestrated by the Minnesota Timberwolves. In step-by-step:
–They traded Mike Conley Jr. + a 1st round pick to the Bulls for “cash”.
–Why would they do this? For two reasons: one above board, one below board.
–Above board: the trade freed up cap room to trade for another Bulls guard, in a separate trade (Ayo Dosunmo). They could not have done that trade, according to cap rules, with Conley on board.
Now the below board, cap and rule circumvention steps:
–The Bulls then re-traded Conley to the Hornets as a ‘throw-in’ portion of a larger trade.
–The Hornets then waived Conley
–Why these moves? Because now Minnesota can re-sign Conley after he was waived. They would not have been allowed to re-sign him if the Bulls cut him. (You can’t re-sign a player you traded…unless that player is re-traded).
There will, of course, be no evidence that Minnesota set this whole process up during the step 1 portion. But, human intuition would say: of course this was all part of Minnesota’s original plan.
And then economically: I challenge any business, anywhere, to have executed a better cost-savings strategy than the Boston Celtics did this year. They left last off-season with a looming $540mm salary + luxury tax bill for this 2025-26 season. Through a series of trades, they have cut that down to $190mm – and have fully avoided the luxury tax. Most amazingly: they are a better team today than they were at end of last year. That is $350mm in savings in one year, with a quality improvement to boot! Unheard of efficiency.
Sadly: the worst part of the NBA overregulation world will now commence. 6-8 teams will spend the rest of the year trying to lose every game. Losing profits in this world, through the ‘logic’ of the NBA draft lottery.
At any rate, a fun day for any NBA fan – but especially for the economically-minded. Incentives matter!
TC again: I would not have expected the major trade stories to involve the Washington Wizards…
Transcript: What an economist eats for lunch (in 2026), with Tyler Cowen—FT
via FT’s The Economics Show with Soumaya Keynes episode page Rules for dining from the world’s foremost foodie economist.